Search anything and hit enter
  • Teams
  • Members
  • Projects
  • Events
  • Calls
  • Jobs
  • publications
  • Software
  • Tools
  • Network
  • Equipment

A little guide for advanced search:

  • Tip 1. You can use quotes "" to search for an exact expression.
    Example: "cell division"
  • Tip 2. You can use + symbol to restrict results containing all words.
    Example: +cell +stem
  • Tip 3. You can use + and - symbols to force inclusion or exclusion of specific words.
    Example: +cell -stem
e.g. searching for members in projects tagged cancer
Search for
Count
IN
OUT
Content 1
  • member
  • team
  • department
  • center
  • program_project
  • nrc
  • whocc
  • project
  • software
  • tool
  • patent
  • Administrative Staff
  • Assistant Professor
  • Associate Professor
  • Clinical Research Assistant
  • Clinical Research Nurse
  • Clinician Researcher
  • Department Manager
  • Dual-education Student
  • Full Professor
  • Honorary Professor
  • Lab assistant
  • Master Student
  • Non-permanent Researcher
  • Nursing Staff
  • Permanent Researcher
  • Pharmacist
  • PhD Student
  • Physician
  • Post-doc
  • Prize
  • Project Manager
  • Research Associate
  • Research Engineer
  • Retired scientist
  • Technician
  • Undergraduate Student
  • Veterinary
  • Visiting Scientist
  • Deputy Director of Center
  • Deputy Director of Department
  • Deputy Director of National Reference Center
  • Deputy Head of Facility
  • Director of Center
  • Director of Department
  • Director of Institute
  • Director of National Reference Center
  • Group Leader
  • Head of Facility
  • Head of Operations
  • Head of Structure
  • Honorary President of the Departement
  • Labex Coordinator
Content 2
  • member
  • team
  • department
  • center
  • program_project
  • nrc
  • whocc
  • project
  • software
  • tool
  • patent
  • Administrative Staff
  • Assistant Professor
  • Associate Professor
  • Clinical Research Assistant
  • Clinical Research Nurse
  • Clinician Researcher
  • Department Manager
  • Dual-education Student
  • Full Professor
  • Honorary Professor
  • Lab assistant
  • Master Student
  • Non-permanent Researcher
  • Nursing Staff
  • Permanent Researcher
  • Pharmacist
  • PhD Student
  • Physician
  • Post-doc
  • Prize
  • Project Manager
  • Research Associate
  • Research Engineer
  • Retired scientist
  • Technician
  • Undergraduate Student
  • Veterinary
  • Visiting Scientist
  • Deputy Director of Center
  • Deputy Director of Department
  • Deputy Director of National Reference Center
  • Deputy Head of Facility
  • Director of Center
  • Director of Department
  • Director of Institute
  • Director of National Reference Center
  • Group Leader
  • Head of Facility
  • Head of Operations
  • Head of Structure
  • Honorary President of the Departement
  • Labex Coordinator
Search

← Go to Research

Go back
Scroll to top
Share
© Research
Publication : Influenza and other respiratory viruses

Mapping influenza activity in emergency departments in France using Bayesian model-based geostatistics.

Scientific Fields
Diseases
Organisms
Applications
Technique

Published in Influenza and other respiratory viruses - 21 Aug 2018

Paireau J, Pelat C, Caserio-Schönemann C, Pontais I, Le Strat Y, Lévy-Bruhl D, Cauchemez S,

Link to Pubmed [PMID] – 30055089

Link to DOI – 10.1111/irv.12599

Influenza Other Respir Viruses 2018 11; 12(6): 772-779

Maps of influenza activity are important tools to monitor influenza epidemics and inform policymakers. In France, the availability of a high-quality data set from the Oscour® surveillance network, covering 92% of hospital emergency department (ED) visits, offers new opportunities for disease mapping. Traditional geostatistical mapping methods such as Kriging ignore underlying population sizes, are not suited to non-Gaussian data and do not account for uncertainty in parameter estimates.Our objective was to create reliable weekly interpolated maps of influenza activity in the ED setting, to inform Santé publique France (the French national public health agency) and local healthcare authorities.We used Oscour® data of ED visits covering the 2016-2017 influenza season. We developed a Bayesian model-based geostatistical approach, a class of generalized linear mixed models, with a multivariate normal random field as a spatially autocorrelated random effect. Using R-INLA, we developed an algorithm to create maps of the proportion of influenza-coded cases among all coded visits. We compared our results with maps obtained by Kriging.Over the study period, 45 565 (0.82%) visits were coded as influenza cases. Maps resulting from the model are presented for each week, displaying the posterior mean of the influenza proportion and its associated uncertainty. Our model performed better than Kriging.Our model allows producing smoothed maps where the random noise has been properly removed to reveal the spatial risk surface. The algorithm was incorporated into the national surveillance system to produce maps in real time and could be applied to other diseases.

Projects